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The ability to measure cognitive load in the workplace provides several opportunities to improve workplace learning. In recent years, virtual reality (VR) has seen an increase in use for training and learning applications due to improvements in technology and reduced costs. This study aims to focus on the use of simulation task load index (SIM-TLX), a recently developed self-reported measure of cognitive load for virtual environments to measure cognitive load while undertaking tasks in different environments.

The authors conducted a within-subject design experiment involving 14 participants engaged in digit-recall n-back tasks (1-back and 2-back) in two VR environments: a neutral grey environment and a realistic industrial ozone facility. Cognitive load was then assessed using the SIM-TLX.

The findings revealed higher task difficulty for the 2-back task due to higher mental demand. Furthermore, a notable interaction emerged between cognitive load and different virtual environments.

This study relied solely on an n-back task and SIM-TLX self-report measure to assess cognitive load. Future studies should consider including ecologically valid tasks and physiological measurement tools such as eye-tracking to measure cognitive load.

Identifying cognitive workload sources during VR tasks, especially in complex work environments, is considered beneficial to the application of VR training aimed at improving workplace learning.

This study provides unique insights into measuring cognitive load from various sources as defined by the SIM-TLX sub-scales to investigate the impact of simulated workplace environments.

The objectives of the proposed model are: aiding nursing staff in documentation tasks, which can be onerous and stressful; and helping management by offering an estimate of the nursing workload, which can be considered for administrative purposes, such as staff scheduling.

An exploratory-descriptive study was conducted in order to identify, investigate, and describe the problem of documenting nursing activities and workload estimation in an intensive care unit. Technological solutions were explored, and models were proposed to address these issues.

Cross-dataset experiments were performed, and the model was able to offer an adequate estimate of the nursing workload. The results suggest that continuous retraining is essential for maintaining high accuracy. While the proposed model was considered in the context of an adult ICU, it can be adapted to other contexts, such as elderly care.

While the proposed solution seems promising, further research is required, such as deploying this system in an ICU and facing challenges in the areas of computer security, medical ethics, and patient data privacy. More patients’ variables could also be collected to improve the workload estimates.

Nursing workload assessment is critical to improve the cost-benefit ratio in health care, offer high-quality patient care, and reduce unnecessary expenses, and this process is usually manual. An automated device can automatically document the amount of time spent in patient care activities in a more transparent, efficient, and accurate manner, freeing staff for more urgent activities and keeping management better informed about day-to-day nursing operations.

In situations where the crew is reduced, the optimization of crew task allocation and sequencing (CTAS) can significantly enhance the operational efficiency of the man-machine system by rationally distributing workload and minimizing task completion time. Existing related studies exhibit a limited consideration of workload distribution and involve the violation of precedence constraints in the solution process. This study proposes a CTAS method to address these issues.

The method defines visual, auditory, cognitive and psychomotor (VACP) load balancing objectives and integrates them with workload balancing and minimum task completion time to ensure equitable workload distribution and task execution efficiency, and then a multi-objective optimization model for CTAS is constructed. Subsequently, it designs a population initialization strategy and a repair mechanism to maintain sequence feasibility, and utilizes them to improve the non-dominated sorting genetic algorithm III (NSGA-III) for solving the CTAS model.

The CTAS method is validated through a numerical example involving a mission with a specific type of armored vehicle. The results demonstrate that the method achieves equitable workload distribution by integrating VACP load balancing and workload balancing. Moreover, the improved NSGA-III maintains sequence feasibility and thus reduces computation time.

The study can achieve equitable workload distribution and enhance the search efficiency of the optimal CTAS scheme. It provides a novel perspective for task planners in objective determination and solution methodologies for CTAS.

Given the growing concern about employees' well-being, numerous researchers have investigated the causes and effects of occupational stress. However, a review study on identifying existing research topics and gaps is still deficient in the extant literature. To fill this gap, this review study aims to present a bibliometric and science mapping approach to review the state-of-the-art journal articles published on occupational stress in the construction industry.

A three-fold comprehensive review approach consisting of bibliometric review, scientometric analysis and in-depth qualitative discussion was employed to review 80 journal articles in Scopus.

Through qualitative discussions, mainstream research topics were summarized, research gaps were identified and future research directions were proposed as follows: versatile stressors and stress model; an extended subgroup of factors in safety behavior; adaptation of multiple biosensors and bio-feedbacks; evaluation and comparison of organizational stress interventions; and incorporation of artificial intelligence and smart technologies into occupational stress management in construction.

The findings of this review study present a well-rounded framework to identify the research gaps in this field to advance research in the academic community and enhance employees' well-being in construction.

Autonomous vehicles (AVs) have the potential to transform the infrastructure, mobility and social well-being paradigms in New Zealand (NZ) amid its unprecedented population and road safety challenges. But, public acceptance, co-evolution of regulations and AV technology based on interpersonal and institutional trust perspectives pose significant challenges. Previous theories and models need to be more comprehensive to address trust influencing autonomous driving (AD) factors in natural settings. Therefore, this study aims to find key AD factors corresponding to the chain of human-machine interaction (HMI) events happening in real time and formulate a guiding framework for the successful deployment of AVs in NZ.

This study utilized a comprehensive literature review complemented by an AV users’ study with 15 participants. AV driving sprints were conducted on low, medium and high-density roads in Auckland, followed by 15 ideation workshops to gather data about the users’ observations, feelings and attitudes towards the AVs during HMI.

This research study determined nine essential trust-influencing AD determinants in HMI and legal readiness domains. These AD determinants were analyzed, corresponding to eight AV events in three phases. Subsequently, a guiding framework was developed based on these factors, i.e. human-machine interaction autonomous driving events relationship identification framework (HMI-ADERIF) for the deployment of AVs in New Zealand.

This study was conducted only in specific Auckland areas.

This study is significant for advanced design research and provides valuable insights, guidelines and deployment pathways for designers, practitioners and regulators when developing HMI Systems for AD vehicles.

This study is the first-ever AV user study in New Zealand in live traffic conditions. This user study also claimed its novelty due to AV trials in congested and fast-moving traffic on the four-lane motorway in New Zealand. Previously, none of the studies conducted AV user study on SUV BMW vehicle and motorway in real-time traffic conditions; all operations were completely autonomous without any input from the driver. Thus, it explored the essential autonomous driving (AD) trust influencing variables in human factors and legal readiness domains. This research is also unique in identifying critical AD determinants that affect the user trust, acceptance and adoption of AVs in New Zealand by bridging the socio-technical gap with futuristic research insights.

Following the imperative for human-centric digital innovation brought by the paradigm of Industry 5.0, the article aims to integrate the dispersed and multi-disciplinary literature on individual risks for workers to define, explain and predict individual risks related to Industry 4.0 technologies.

The paper follows the question, “What is the current knowledge and evidence base concerning risks related to Industry 4.0 technologies, and how can this inform digital innovation management in the manufacturing sector through the lens of the Industry 5.0 paradigm?” and uses the method of systematic literature review to identify and discuss potential risks for individuals associated with digital innovation. N = 51 contributions met the inclusion criteria.

The literature review indicates dominant trends and significant gaps in understanding risks from a human-centric perspective. The paper identifies individual risks, their interplay with different technologies and their antecedents at the social, organizational and individual levels. Despite this, the paper shows how the literature concentrates in studying risks on only a limited number of categories and/or concepts. Moreover, there is a lack of consensus in the theoretical and conceptual frameworks. The paper concludes by illustrating an initial understanding of digital innovation via a human-centered perspective on psychological risks.

Findings yield practical implications. In investing in the adoption, generation or recombination of new digital technologies in organizations, the paper recommends managers ensure to prevent risks at the individual level. Accordingly, the study’s findings can be used as a common starting point for extending the repertoire of managerial practices and interventions and realizing human-centric innovation.

Following the paradigm of Industry 5.0, the paper offers a holistic view of risks that incorporates the central role of the worker as crucial to the success of digital innovation. This human-centric perspective serves to inform the managerial field about important factors in risk management that can result in more effective targeted interventions in risk mitigation approaches. Lastly, it can serve to reinterpret digital innovation management and propose future avenues of research on risk.

This study explored the influence of personalized virtual try-on (PVTO) technology on consumer behavior in the apparel industry, focusing on decision comfort. It investigated how individuals’ spatial processing perception acts as a moderator in this context. Additionally, it examined the ease with which individuals imagine a product within the framework of this psychological mechanism.

Two experimental studies were conducted to evaluate the effects of PVTO technology on consumer decision comfort, with spatial processing perception as a moderating variable. The first experiment (n = 252) explored the impact of PVTO on decision comfort using photo-based simulations across various apparel items. The second experiment (n = 125) further examined these effects using measurement-based PVTO technologies to provide a deeper understanding of the role of spatial processing. Both studies employed a between-subjects design to isolate the influence of PVTO technology from other variables, ensuring a focused analysis of its effects on consumer behavior.

The findings indicated that the effects of PVTO are stronger for consumers with lower spatial perception abilities. Ease of imagining a product was identified as a mediator in the interactive effect between PVTO and spatial perception on decision comfort, demonstrating its pivotal role in online apparel shopping.

The findings indicated that the effects of PVTO are stronger for consumers with lower spatial perception abilities. Ease of imagining a product was identified as a mediator in the relationship between PVTO and decision comfort, demonstrating its pivotal role in online apparel shopping.

Increasing personnel costs and labour shortages have pushed retailers to give increasing attention to their intralogistics operations. We study hybrid order picking systems, in which humans and robots share work time, workspace and objectives and are in permanent contact. This necessitates a collaboration of humans and their mechanical coworkers (cobots).

Through a longitudinal case study on individual-level technology adaption, we accompanied a pilot testing of an industrial truck that automatically follows order pickers in their travel direction. Grounded on empirical field research and a unique large-scale data set comprising N = 2,086,260 storage location visits, where N = 57,239 storage location visits were performed in a hybrid setting and N = 2,029,021 in a manual setting, we applied a multilevel model to estimate the impact of this cobot settings on task performance.

We show that cobot settings can reduce the time required for picking tasks by as much as 33.57%. Furthermore, practical factors such as product weight, pick density and travel distance mitigate this effect, suggesting that cobots are especially beneficial for short-distance orders.

Given that the literature on hybrid order picking systems has primarily applied simulation approaches, the study is among the first to provide empirical evidence from a real-world setting. The results are discussed from the perspective of Industry 5.0 and can prevent managers from making investment decisions into ineffective robotic technology.

Our study addresses the impact of COVID-19-induced work-family conflict on leaders' well-being and explores the influence of leadership style, coping strategies, and gender disparities in this context, filling a research gap on crisis-related leadership well-being.

We used hierarchical regression analysis and SPSS's PROCESS macro to analyze a dataset of 516 paired responses, including 231 leaders and 285 subordinates, from Mongolian organizations.

Strain-based work-family conflict (WFC) negatively affects leaders' workplace well-being. Servant leadership exacerbates this impact. In contrast, servant leadership positively moderates the relationship between time-based WFC and job-related well-being. Leaders who prioritize work and family responsibilities experience a stronger positive (negative) impact of time-based (strain-based) WFC on their workplace well-being. Furthermore, we observed that strain-based WFC has a more detrimental effect on female leaders' well-being, highlighting gender disparities in leadership roles.

Our study elucidates the intricate relationship between work-family conflict and leaders' well-being, underscoring the need to recognize gender differences and coping strategies. We advocate for organizations to proactively establish support structures tailored to various leadership styles and gender-specific challenges, especially in times of crisis.

This study focuses on leaders' well-being during COVID-19 and how it is influenced by work-family conflict, servant leadership, coping strategy, and gender. The study also differentiates between time-based and strain-based work-family conflict and uses dyadic data from Mongolian organizations. More importantly, we identify that gender disparity plays a crucial role in the pandemic-caused leadership challenges and leaders' coping behaviors.

The purpose of this research is to investigate the acceptance and support of neurodiverse people in society, with a focus on autism, and to use this to propose a framework to enhance inclusivity that can inform pedagogy within the education sectors.

Three case studies from higher education have been presented and mapped onto a multi-dimensional spectrum of characteristics normally associated with autistic people. Further examples have been taken from the general population and these have been used, along with user scenarios to propose a framework for inclusivity.

A framework, the human spectrum, has been proposed which encompasses all of society, regardless of diagnoses and within which people have mobility in terms of their characteristics. It is proposed that this framework should be incorporated into pedagogy in primary, secondary and tertiary education so that teaching and assessment is inclusive and so that people’s understanding of human nature is built from an early age to counter stigma and herd mentality, or othering.

The contribution of this paper could have significant implications for society as the framework provides a structure to enable people to consider others with new perspectives.

The framework proposed provides a new and original way of shaping the way people think within the education sector and elsewhere.